3
Tools for Virtual Design and Manufacturing

Five technical domains have been identified in which virtual design and manufacturing tools exist or where important areas of knowledge and practice are supported by information technology: systems engineering, engineering design, materials science, manufacturing, and life-cycle assessment. However, progress is needed in order to more fully take advantage of these models, simulations, databases, and systematic methods. Each of the domains is largely independent of the others, although links are being made, bridges are being built, and practitioners and researchers in each domain recognize the value of knowledge in some of the other domains. Intercommunication and interoperability are two prerequisites for serious progress. Formidable technical and nontechnical barriers exist, and the committee offers recommendations in each domain.

TOOL EVOLUTION AND COMPATIBILITY

Throughout human history tools have evolved, typically driven by technological availability, market dynamics, and fundamental need. In agriculture, teams of oxen have been replaced by sophisticated tractors with specialized attachments. Computing tools have morphed from fingers and toes to abacuses to slide rules to calculators to high-performance computers. The software used within these computing systems has evolved in terms of programming levels of abstraction and overall functionality. Software not only is written as an end item that operates within a product, but now also gets developed as models and simulations to emulate the end item itself in order to perfect its eventual production, field use, and retirement. Software-based tools are developed to create and use these models and simulations to best perform design, engineering analyses, and manufacturing. Table 3-1 lists examples of available tools and the areas in which they operate.

Advanced engineering environments (AEEs) are integrated computational systems and tools that facilitate design and production activities within and across organizations. An AEE may include the following elements:

  • Design tools such as computer-aided design (CAD), computer-aided engineering (CAE), and simulation

  • Production tools such as computer-aided manufacturing (CAM), manufacturing execution system, and workflow simulation



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Retooling Manufacturing: Bridging Design, Materials, and Production 3 Tools for Virtual Design and Manufacturing Five technical domains have been identified in which virtual design and manufacturing tools exist or where important areas of knowledge and practice are supported by information technology: systems engineering, engineering design, materials science, manufacturing, and life-cycle assessment. However, progress is needed in order to more fully take advantage of these models, simulations, databases, and systematic methods. Each of the domains is largely independent of the others, although links are being made, bridges are being built, and practitioners and researchers in each domain recognize the value of knowledge in some of the other domains. Intercommunication and interoperability are two prerequisites for serious progress. Formidable technical and nontechnical barriers exist, and the committee offers recommendations in each domain. TOOL EVOLUTION AND COMPATIBILITY Throughout human history tools have evolved, typically driven by technological availability, market dynamics, and fundamental need. In agriculture, teams of oxen have been replaced by sophisticated tractors with specialized attachments. Computing tools have morphed from fingers and toes to abacuses to slide rules to calculators to high-performance computers. The software used within these computing systems has evolved in terms of programming levels of abstraction and overall functionality. Software not only is written as an end item that operates within a product, but now also gets developed as models and simulations to emulate the end item itself in order to perfect its eventual production, field use, and retirement. Software-based tools are developed to create and use these models and simulations to best perform design, engineering analyses, and manufacturing. Table 3-1 lists examples of available tools and the areas in which they operate. Advanced engineering environments (AEEs) are integrated computational systems and tools that facilitate design and production activities within and across organizations. An AEE may include the following elements: Design tools such as computer-aided design (CAD), computer-aided engineering (CAE), and simulation Production tools such as computer-aided manufacturing (CAM), manufacturing execution system, and workflow simulation

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Retooling Manufacturing: Bridging Design, Materials, and Production TABLE 3-1 Representative Tools Used in the Industry System Life Cycle Engineering/Technical Cost Analysis systems Engineering   Activity Marketing Product Engineering Industrial Engineering Marketing   Function Action Mission, or Customer Needs Requirements Analysis Product Planning Functional Analysis Product Architecture Synthesis Engineering Design Analysis, Visualization, and Simulation Manufacturing Engineering Analysis and Visualization Manufacturing Operations Production and Assembly Field Operations Use, Support, and Disposal Business Case Forecasting @Risk, Crystal Ball, Excel, i2, Innovation Management, JD Edwards, Manugistics, Oracle, PeopleSoft, QFD/Capture, RDD-SD, SAP, Siebel Arena PLM, Eclipse CRM, Innovation Management, MySAP PLM, RDD-SD, specDEV, TRIZ Arena PLM, Innovation Management, MySAP PLM, RDD-IDTC, specDEV, TRIZ Arena PLM, Innovation Management, MySAP PLM, RDD-IDTC, specDEV, TRIZ Arena PLM, Innovation Management, MySAP PLM, specDEV, TRIZ Arena PLM, MySAP PLM, specDEV, TRIZ Innovation Management Product Life-Cycle Planning and Management Innovation Management, QFD/Capture, RDD-RM Geac, I-Logix, Innovation Management, Invensys, JD Edwards, Oracle, PeopleSoft, RDD-SA, SAP, Windchill Innovation Management, RDD-SD Functional Prototyping, RDD-SD Functional Prototyping   Innovation Management, RDD-SD Resource Planning Project, RDD-DVF, RDD-SD, TaskFlow Management Innovation Management, RDD-DVF, RDD-SD DSM, Geac, Invensys, JD Edwards, Oracle, People Soft, RDD-SD, SAP, TaskFlow Management DSM, Project, RDD-SD, TaskFlow Management TaskFlow Management, HMS-CAPP TaskFlow Management TaskFlow Management Computer-aided engineering Modeling Caliber, DOORS, RDD-SD, RDD-OM, Innovation Management, Statemate Caliber, DOORS, Innovation Management, RDD-OM, Statemate ADAMS, Caliber, DADS, DOORS, Dynasty, EASA, Engineous, Innovation Management, LMS, MatLab, MSC, Opnet, Phoenix, RDD-OM, RDD-SD, Statemate, VL Abaqus, AML, Ansys, AutoCAD, AVL, Caliber, CATIA, DOORS, EASA, EDS, Engineous, Fluent, Functional Prototyping, IDEAS, MSC, Opnet, Phoenix, ProE, RDD-SD, StarCD, Statemate, Unigraphics, Working Model Caliber, DFMA, DOORS, Functional Prototyping Caliber, DOORS Caliber, DOORS, Innovation Management

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Retooling Manufacturing: Bridging Design, Materials, and Production System Life Cycle Engineering/Technical Cost Analysis Systems Engineering   Activity Marketing Product Engineering Industrial Engineering Marketing   Function Action Mission, or Customer Needs Requirements Analysis Product Planning Functional Analysis Product Architecture Synthesis Engineering Design Analysis, Visualization, and Simulation Manufacturing Engineering Analysis and Visualization Manufacturing Operations Production and Assembly Field Operations Use, Support, and Disposal Computer-aided engineeing Simulation Caliber, DOORS, Innovation Management, RDD-DVF, Statemate Caliber, DOORS, Innovation Management, RDD-DVF, Statemate, Working Model Caliber, DOORS, CATIA, Delmia V5, Enovia V5, RDD-SD, Innovation Management, Statemate Abaqus, AML, ANSoft, Ansys, Caliber, DICTRA, DOORS, DYNA3D, EASA, EDS, Engineous, Functional Prototyping, ICEM CFD, LMS, ModelCenter, MSC, NASTRAN, Phoenix, RDD-SD, Statemate, Stella/Ithink Caliber, DOORS, Functional Prototyping, HMS-CAPP Caliber, DOORS Caliber, DOORS, Innovation Management Visualization Innovation Management, RDD-OM, Statemate Innovation Management, RDD-OM, RDD-SD, Statemate CATIA, Delmia V5, EDS, Enovia V5, Innovation Management, Jack, RDD-SA, Slate, Statemate Abaqus, ACIS, Amira, Ansys, EDS, EnSight, Fakespace, Functional Prototyping, Ilogix, Jack, MatLab, Open-DX, RDD-SD, Rhino, SABRE, Simulink, Slate, Statemate, VisMockup Functional Prototyping, Statemate   Innovation Management Computer-aided manufacturing Product Data Management Innovation Management Innovation Management CATIA, Delmia V5, Enovia V5 CATIA, Dassault, Delmia V5, EDS, Enovia V5, Metaphase, PTC, Windchill     Innovation Management Electronic Design Automation Caliber, DOORS Caliber, DOORS, MatLab Caliber, Doors, Integrated Analysis, Simulator, Verilog-XL Cadence, Caliber, Dassault, DOORS, Integrated Analysis, Neteor Graphics, PTC, System Vision Caliber, DOORS Caliber, DOORS, PADS Caliber, DOORS, Integrated Analysis Manufacturing System Design Functional Prototyping, RDD-ITDC, RDD-SD Innovation Management, RDD-ITDC, RDD-SD Integrated Data Sources, RDD-ITDC, RDD-SD CimStation, Envision/Igrip, Integrated Data Sources, RDD-ITDC, RDD-SD CIM Bridge, EDS, Tecnomatix   Functional Prototyping

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Retooling Manufacturing: Bridging Design, Materials, and Production Computer-aided manufacturing Manufacturing System Modeling Functional Prototyping, RDD-ITDC, RDD-SD Functional Prototyping, RDD-ITDC, RDD-SD DICTRA, Functional Prototyping, Pandat, RDD-ITDC, RDD-SD, Thermo-Calc Abinitio, CimStation, Dante, DEFORM, Envision/Igrip, Functional Prototyping, MAGMA, ProCast, RDD-ITDC, RDD-SD, SysWeld Abinitio, Arena, Dante, DEFORM, Extend, Functional Prototyping, MAGMA, Pro/ Model, ProCast, Simul8, SysWeld, TaylorED, Witness Abinitio, Dante, DEFORM, Functional Prototyping, MAGMA, ProCast, SysWeld Functional Prototyping Manufacturing System Simulation   Functional Prototyping Caliber, DOORS, Functional Prototyping Abinitio, Caliber, CimStation, Dante, DEFORM, DOORS, Envision/Igrip, MAGMA, ProCast, SysWeld Abinitio, Arena, Caliber, Dante, DEFORM, DOORS, Extend, MAGMA, Pro/Model, ProCast, Simul8, SysWeld, TaylorED, Witness Abinitio, Dante, DEFORM, MAGMA, ProCast, SysWeld   Manufacturing System Visualization Functional Prototyping Functional Prototyping Functional Prototyping CimStation, Envision/Igrip, Functional Prototyping Arena, Extend, Functional Prototyping, Pro/Model, Simul8, Taylor ED, Witness Abinitio, Functional Prototyping, MAGMA, ProCast, SysWeld Functional Prototyping Reliability Models RDD-ITDC, RDD-SD Functional Prototyping, RDD-ITDC, RDD-SD DEFORM, DisCom2, Functional Prototyping, RDD-ITDC, RDD-SD CASRE, Functional Prototyping, RDD-ITDC, RDD-SD   JMP, Minitab, SAS, WinSMITH RDD-ITDC, RDD-SD Logistics Eclipse ERP, Integrated Analysis, RDD-ITDC, RDD-SD Integrated Analysis, RDD-ITDC, RDD-SD RDD-ITDC, RDD-SD Integrated Analysis, RDD-ITDC, RDD-SD Integrated Analysis JD Edwards, Logistics, Manugistics Integrated Analysis, RDD-ITDC, RDD-SD Purchasing Purchasing plus         I2, Invensys, JD Edwards, Oracle, PeopleSoft, PTC, SAP   Supervisory Control       QUEST   Invensys, Siemens   Machine Control       Virtual NC   Labview, MATLAB, Unigraphics  

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Retooling Manufacturing: Bridging Design, Materials, and Production Program management tools such as configuration management, risk management, and cost and schedule control Data repositories storing integrated data sets Communications networks giving participants inside and outside the organization secure access to data As shown in Table 3-1, most of these tools exist today, but an AEE is more than just a collection of independent tools. Tools must be integrated to provide interoperability and data fusion. Organizational and interorganizational structures must be configured to reward their use and workforce skills must be enhanced to make effective use of their capabilities.1 The Carnegie Mellon University Software Engineering Institute (SEI) studied the use of AEEs and concluded that they exist within a broad domain, across all aspects of an organization. AEEs provide comprehensive coverage of and substantial benefits to design and manufacturing activities: Office applications such as word processing, spreadsheets, and e-mail, are already familiar to nearly everyone. Computer-aided design and integrated solid modeling not only improve the quality of the engineering product but also provide the basis for the exchange of product data between manufacturers, customers, and suppliers. Computer-aided engineering enables prediction of product performance prior to production, providing the opportunity for design optimization, reducing the risk of performance shortfalls, and building customer confidence. Manufacturing execution systems provide agile, real-time production control and enable timely and accurate status reporting to customers. Electronic data interchange provides up-to-date communication of business and technical data among manufacturers, customers, and suppliers. Information security overlays all operations to keep data safe. Figure 3-1 is a modification of an SEI chart presented to the committee that helps show the widespread and pervasive use of software that bridges many functions and levels throughout the design and manufacturing enterprise. Enterprise viewpoints concentrate on near-term, mid-term, and far-term perspectives in the context of factory floor execution, tactical analysis, and strategic thinking, respectively. A product's evolution typically is split into many phases to show its various stages, and most tools can be categorized in terms of the temporal nature of their use. In this case, the committee has elected to view a product's life cycle as shown here in seven stages, from mission needs to field operations. Figure 3-1 shows that there is little overlap between manufacturing modeling and simulation tools, or manufacturing process planning, and engineering design tools, reflecting the lack of interoperability between these steps with currently available software. Many vendors sell tools that are now beginning to offer intriguing solutions toward overlap of key functions. Table 3-1 shows representative examples of some of these tools now being used in industry.2 For example, to address CADCAE interoperability, process integration and 1   National Research Council, Advanced Engineering Environments: Achieving the Vision, Phase 1, National Academy Press, Washington, D.C., 1999. 2   In addition, Appendix C describes some of the current engineering design tools and Appendix D provides a list of representative vendors of computer-based tools used for design and other functions.

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Retooling Manufacturing: Bridging Design, Materials, and Production FIGURE 3-1 Overlay of tools that bridge design and manufacturing. Each ellipse within the chart represents a different tool category. Ellipse size connotes the comprehensiveness of the capabilities of those tools within the matrix, and color shading (or lack thereof) highlights the focus of the various tools’ strengths in design, manufacturing, business operations, or management. Blue shades indicate a concentration in design, while green trends into manufacturing. Yellow hues show a proclivity toward business operations. Orange indicates the prominence and importance of data management. Ellipses void of color detail project management functions. Source: Special permission to reproduce figure from “Advanced Engineering Environments for Small Manufacturing Enterprises,” © 2003 by Carnegie Mellon University, is granted by the Software Engineering Institute. design optimization software tools that bundle discrete tools in order to facilitate multiprocess optimization are being introduced. Examples of such software are Synaps/Epogy, Isight, and Heeds from Red Cedar Technology. While these software packages look attractive in principle, human input still becomes essential to bridge the gaps between various analytical tools. This chapter covers in depth the state of affairs within each of five different tool categories: The section titled "Systems Engineering Tools" explains how philosophies are expanding from narrow discrete-element minimization to design-trade-space optimization strategies and, while many tools exist within their own specialized field, recommends the need for supervisory control and common links between individual routines. "Engineering Design Tools" discusses the current capabilities of engineering design methods and software and their general lack of interoperability. It makes recommendations to improve communication between design and manufacturing software so that engineering models can be exchanged and simulated in multiple

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Retooling Manufacturing: Bridging Design, Materials, and Production environments. "Materials Science Tools" describes how properties of materials limit the design process and recommends improved physical models and property databases to support virtual design and manufacturing. "Manufacturing Tools" portrays advances in software ranging from detailed process planning and simulation models through production and enterprise management systems, focusing explicitly on issues related to the scope and scale of tools to design for X (DfX), where X is a variety of manufacturing parameters. It recommends organizational and algorithmic approaches for addressing obstacles. "Life-Cycle Assessment Tools" measures the total environmental impact of manufacturing systems from the extraction of raw materials to the disposal of products and evaluates product and process design options for reducing environmental impact. SYSTEMS ENGINEERING TOOLS The phrase, topic, and discipline "systems engineering" in the context of industrial manufacturing has evolved over the last several decades such that it now includes more topics and encompasses a far greater portion of the product life cycle than Henry Ford probably could have envisioned in 1914. By 1980, systems engineering thinking in this context was expanding; but it was still essentially limited to the industrial engineering skill of maximizing production to minimize cost by minimizing the time required to perform each individual manufacturing step or assembly action. The underlying assumption was that minimizing the time required for each discrete event would also minimize the total cost to manufacture an item. As such, the concepts were not applicable until production commenced and then they were only applied to minimize the cost after the product was designed and the manufacturing process or assembly line was defined. Systems engineering and the discrete event minimization strategy in the early 1900s could not have predicted Henry Ford's departure from a traditional batch assembly philosophy to the assembly line concept. Even though the resultant unit cost was dramatically reduced, the significant increases in time to first article, cost to design, and cost of construction were seen as insurmountable barriers. The assembly line was an unpredictable revolutionary change from the evolutionary manufacturing improvements associated with discrete event minimization. During the last two decades, systems engineering has evolved to include the cost of automated machine tools as alternatives to labor and has developed several very different cost profiles; but the optimizations were still being performed at the simple part or discrete work element level. And the evaluations were being conducted on an essentially static, or already designed and about to be built, factory. While computers had become readily available in the 1980s, there were no fundamental changes in the process of minimizing the discrete events to minimize the total cost. The computers only crunched more numbers. Today's hardware and software are capable of simulating multiple, if not essentially unlimited, factory designs and equipment variations, giving the systems engineer the ability to affect both prior to a factory's construction. When the full costs of labor, shipping, and work in process are included in the evaluations, the systems engineer can also affect the manufacturing site selection. But the same discrete-element minimization mentality remains. Current thinking and research in systems engineering are beginning to expand the scope from focusing on discrete work elements to analyzing entire operations, lines, factories, or enterprises to optimize the total cost of a given design or set of designs. With the continuously increased speed and lowered cost of computing, this is generally possible. But the task is being performed by brute-force methodology whereby all known permutations and combinations of discrete events are tried and all but the best are excluded.

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Retooling Manufacturing: Bridging Design, Materials, and Production FIGURE 3-2 Expanded systems engineering phases. Source: B.S. Blanchard and W.F. Fabrycky, Systems Engineering and Analysis, 3rd Edition, © 1998. Reprinted by permission of Pearson Education Inc., Upper Saddle River, N.J. During the last 10 years, systems engineering has matured to the point that it is not an uncommon degree program in universities. Industry and defense both utilize the discipline, and there is a globally recognized organization that represents the practitioners. The International Council on Systems Engineering (INCOSE) defines the subject as "… an interdisciplinary approach and means to enable the realization of successful systems." Further, INCOSE lists seven functional areas included in systems engineering (operations, performance, testing, manufacturing, cost and scheduling, training and support, and disposal).3 Blanchard and Fabrycky bring many of the systems engineering concepts and phases together in their book as shown in Figure 3-2. Other authors have described systems engineering as having four (Figure 3-3), seven (Figure 3-1), and even eight (Figure 3-4) phases. The important factors to observe from all this are that systems engineering can include everything from determination of the need for a product to its disposal, and that there are significant overlapping phases (notably design and manufacturing) that require interconnections and the sharing of data and information. Engineering Cost Analysis The next logical advance is what is referred to as an engineering or technical cost analysis. In its simplest form, it may be no more than a spreadsheet listing the phases found in the product concept through product realization cycles on one axis and identifying the many functional areas, costs, or even software tools on the other. This committee elected to settle on seven phases and portray the traditional flow of effort (time) from left to right as shown in Table 3-1: function; mission or customer needs; product planning; product architecture; engineering design; manufacturing engineering; manufacturing operations; and field operations. 3   International Council on Systems Engineering. Available at: http://www.incose.org. Accessed April 2004.

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Retooling Manufacturing: Bridging Design, Materials, and Production FIGURE 3-3 Life-cycle phases collapsed into four. Source: R. Garrett, Naval Surface Warfare Center, "Opportunities in Modeling and Simulation to Enable Dramatic Improvements in Ordnance Design," presented to the Committee on Bridging Design and Manufacturing, National Research Council, Washington, D.C., April 29, 2003. A significant number of companies are already identifying where there is a need to communicate and work together both within the company divisions and with other companies. In its second-generation form, engineering cost analysis software will approximate the costs associated with each phase of the product development–realization cycle. In its ultimate form, the engineering cost analysis will include and improve upon all of systems engineering's current discrete event optimization functions; but, more importantly, it will extend forward in time to include accurate estimates for various design, material, and process selection options. In some instances, it may also include the determination of the optimum product concept to satisfy the intended customers' needs and cost constraints. Numerous presentations to the committee made the point that increased and improved communications between all phases will significantly reduce the time from concept to first article. Some examples of time savings that have already been achieved were presented to the committee:4 Chrysler, Ford, and GM have reduced the interval from concept approval to production from 5 to 3 years. Electric Boat has been able to cut the time required for submarine development in half—from 14 years to 7 years. 38 Sikorsky draftsmen took 6 months to develop working drawings of the CH-53E Super Stallion's outside contours. With virtual modeling and simulation, a single engineer accomplished the same task for the RAH-66 Comanche Helicopter in 1 month. 14 engineers at the Tank and Automotive Research and Development Center designed a low-silhouette tank prototype in 16 months. By traditional methods this would have taken 3 years and 55 engineers. Northrop Grumman's CAD systems provided a first-time, error-free physical mockup of many sections of the B2 aircraft. The U.S. Navy's modeling and simulation processes for the Virginia-class submarine reduced the standard parts list from ~95,000 items for the earlier Seawolf-class submarine to ~16,000 items. It is necessary to provide the engineer at the CAD terminal with new and improved software tools that can give guidance regarding the life-cycle costs of each design decision in both preliminary and detailed design. For example, specific data could be made available to the designer regarding the alternative costs of various manufacturing approaches such as 4   M. Lilienthal, "Observations on the Uses of Modeling and Simulation," presented to the Committee on Bridging Design and Manufacturing, National Research Council, Washington, D.C., February 24, 2003.

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Retooling Manufacturing: Bridging Design, Materials, and Production FIGURE 3-4 Life-cycle phases expanded into the eight indicated at the top of the figure. Source: A. Adlam, U.S. Army, "TACOM Overview," presented to the Committee on Bridging Design and Manufacturing, National Research Council, Washington, D.C., June 25-26, 2003. automatic tape lay-up, injection molding, or electron beam welding, which could be selected to reduce unit manufacturing costs. In addition, reliability data for such proven components as hydraulic actuators, electrical connectors, and generators could easily be made available through interconnected databases to achieve a first-cut design that was reliable, maintainable, and low cost. This would be a huge step towards giving customers low total life-cycle costs. It is critical to note, and generally ignored, that the geometrical shape of a part or assembly will determine the subsequent manufacturing processes by which it may be made and will, inadvertently, limit the materials to just those few that are suitable for those processes. This limitation has led to the rule of thumb that the majority of cost reduction opportunities are lost at the time a part is designed. Frequently, multiple design concepts or design/material combinations will satisfy a desired function. For that reason, it is imperative that all design options, along with their associated manufacturing processes and materials, be evaluated prior to committing to a final design strategy. Again, several presentations to this committee emphasized the importance of improving the assessment of needs and the exploration of the design trade space and a means to minimize total life-cycle costs. Figure 3-5 shows one author's views on when and where the full cost of a product is locked in. Other authors provided additional guidelines to support the value of up-front design analysis. Some guidelines presented to the committee5,6 are listed below: 5   J. Hollenbach, "Modeling and Simulation in Aerospace," presented to the Committee on Bridging Design and Manufacturing, National Research Council, Washington, D.C., February 24, 2003. 6   A. Haggerty, "Modeling the Development of Uninhabited Combat Air Vehicles," presented to the Committee on Bridging Design and Manufacturing, National Research Council, Washington, D.C., April 29, 2003.

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Retooling Manufacturing: Bridging Design, Materials, and Production FIGURE 3-5 Product cost locked in very early in process. Source: M. Lilienthal, Defense Modeling and Simulation Office, “Observations on the Uses of Modeling and Simulation," presented to the Committee on Bridging Design and Manufacturing, National Research Council, Washington, D.C., February 24-25, 2003. Continue the early collaborative exploration of the largest possible trade space across the life cycle, including manufacturing, logistics, time-phased requirements, and technology insertion. Perform assessments based on modeling and simulation early in the development cycle—alternative system designs built, tested and operated in the computer before critical decisions are locked in and manufacturing begins. Wait to develop designs until requirements are understood. Requirements are the key. Balance them early! Once the design is drawn, the cost and weight are set. No amount of analysis can help a bad design get stronger or cheaper. Remember that 80 percent of a product's cost is determined by the number of parts, assembly technique, manufacturing processes, tooling approach, materials, and tolerances. The linkages between design, manufacturing, and materials, combined with the value of reaching the customer in the least amount of time, support a robust business case for quick development of initial products. This increased effort at the start would be at a higher than optimal initial cost, but with scheduled updates and design changes would result in future improved reliability and cost while maintaining service part commonality. This approach could also result in the discovery of design and manufacturing strategies corresponding to an immediate need; when the product development cycle is shortened, products can be designed

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Retooling Manufacturing: Bridging Design, Materials, and Production domains, fundamental knowledge is still lacking. Research is needed to develop efficient scheduling algorithms that permit rapid redirection of resources to meet changing demands or circumstances; models of assembly tasks performed by people to understand fatigue, errors, and injuries; design of factories to permit flexibility and efficient redeployment of large investments; and generalizations of existing design-for-X (DfX) methods and rule bases to include such concerns as product quality, recycling, and environmental friendliness. Bridging of Design and Manufacturing The bridging of design and manufacturing is a core issue for this study. It is not represented by an explicit step in conventional definitions of product development, except perhaps in design-for-X (DfX) processes. Instead, ideally, it is a pervasive activity that should occur continuously throughout product development. The committee notes that each identified activity is carried out now, but the degree to which tools exist in automated form varies greatly. Moreover, the lack of understanding of cultural and managerial barriers may be more important than lack of computer tools. Technical Coordination of Specifications and Procedures Some of these coordination activities include the following: Identification of critical resources such as suppliers, factories, long lead items, and employees' skills needed to manufacture a given design Identification of design and materials alternatives or process alternatives needed to manufacture a given design, together with ways of finding the best combination Determination of the structure of product families and architectures to coordinate with layout, equipment, and organization of the factory to permit flexibility and efficient redeployment of assets to meet changing requirements Alignment of materials properties specifications and production outputs, tolerances on parts and resulting variation, and tolerances on assemblies and resulting variation Collection and utilization of lessons learned during product launch Collection and utilization of lessons learned during use of the product There is a race between advancing knowledge and rising expectations regarding product quality and performance. As customers' expectations rise, tolerances that used to be sufficient are now no longer acceptable. Competition drives all players to be as good as the leaders. Better understanding of materials and processing methods will grow incrementally, as it has in the past. Breakthroughs in conventional materials are unlikely, and adoption of new materials in existing industries is notoriously slow. Stand-alone computer tools will emerge when knowledge becomes stable. Adoption of such tools will depend on ease of learning and use and on the relevance of what the tool does and what the company requires its employees to do. Organizational barriers and incorrectly structured incentives may inhibit the adoption of tools and methods. Many companies outsource the design and construction of manufacturing equipment and systems, often because manufacturers no longer have the capability. But capability was lost when the decision was made to outsource to begin with. Outsourcing of tightly coupled activities

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Retooling Manufacturing: Bridging Design, Materials, and Production adds complexity to an already complex bridging process.43 This trend is expected to continue, although some companies are trying to regain lost capabilities. Organizational and Managerial Arrangements, and Enablers of Bridging There are a number of organizational and managerial arrangements that need to be considered: Methods of analyzing design processes to identify inefficiencies such as missing information and unnecessary repetitions of process steps Economic models of cost versus value in revising production processes and investments to improve the product Skills and training in negotiation Definition of roles and responsibilities that bridge conventional organizational boundaries between design and manufacturing In this domain there is continual flux and reconceptualization of objectives and methods. Lean manufacturing and agile manufacturing are two suggested ways of organizing manufacturing enterprises for the best delivery of value. Within lean manufacturing, one suggested concept is value stream mapping. This technique aims to identify all the steps and actors in creation of an object or a piece of information in order to find inefficiencies and eliminate waste. This is a domain in which enlightened practitioners often lead researchers, who serve to observe, report, and systematize what they observe in order to improve the performance of other companies. Here, again, there is a race between capabilities and expectations. In particular, companies want to develop products faster. In the car industry, it typically takes about 4 years to go from concept to production. One of the longest steps in car development is evaluation of the manufacturing feasibility of the design, which sometimes takes 2 years. Great improvements in streamlining this process have been achieved by introducing computational tools. At the same time, new requirements for safety, durability, and appearance have made the task harder. Also, much if not most of the value of cars and aircraft is outsourced, requiring coordination of design and manufacturing across many organizational boundaries. This extra set of transactions increases the complexity. The result is that the process is not significantly faster than it was 10 years ago. However, some aircraft companies using the results of the USAF/MIT Lean Aerospace Initiative with integrated analysis tools have now designed and developed new prototype aircraft such as the X-32, X-45, and X-47 in approximately half the schedule and half the cost of traditional methods. Also, some car companies can bring out new versions of existing cars in as few as 2 years. The reasons appear to be a combination of more astute use of computational tools plus managerial techniques such as coordination of tasks, reuse of existing designs and factories, smart supply chain management, and incentives for design and manufacturing engineers to work more closely together.44 As another example, the new Boeing 7E7 commercial transport is planned to be in final assembly for only 3 days, reflecting the culmination of the lean enterprise transformation of lean engineering, lean supply chain, and 43   Charles Fine and Daniel Whitney, "Is the Make-Buy Decision a Core Competence?" Moreno Muffatto and Kulwant Pawar (eds.), Logistics in the Information Age, Servizi Grafici Editoriali, Padova, Italy, 1999, pp. 31-63. 44   Durward K. Sobek II, "Principles That Shape Product Development Systems: A Toyota-Chrysler Comparison," PhD Thesis, University of Michigan, 1997; J.M. Morgan, "High Performance Product Development: A Systems Approach to a Lean Product Development Process," PhD Thesis, University of Michigan, 2002.

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Retooling Manufacturing: Bridging Design, Materials, and Production lean manufacturing. Improvement in design–manufacturing coordination involves both technical and managerial/organizational actions. Creation of new technical knowledge in this domain will not be sufficient without accompanying improvements in management methods and organizational arrangements. These include how to structure cross-functional teams, how to flow information in a timely manner between team members, how to identify and resolve conflicts and discrepancies, and so on. These are ongoing research topics in business schools and some engineering schools. These activities should be encouraged. Research on outsourcing of key activities to determine how to minimize complexity and maximize coordination is also needed, along with better economic models of outsourcing choices that reflect the strategic impacts on companies and industries. Loss of national capability also needs to be assessed. Recommendation 4. Manufacturing: The Department of Defense should assess the role and impact of outsourcing on the integration of manufacturing and design functions. Assessing the impact of outsourcing key activities can help determine how to minimize complexity and maximize coordination in various organizational structures between manufacturing systems. Tools that include efficient algorithms for production scheduling and procedures for flexible factory design can ease the difficulties of outsourcing. LIFE-CYCLE ASSESSMENT TOOLS This section deals with the evaluation of the environmental impact of a product over its life cycle from concept to disposal and not with life-cycle design or life-cycle analysis, which is a broader topic that encompasses life-cycle costing, design for reliability, design for maintainability, and life-cycle analysis. Some aspects of life-cycle design are addressed in the earlier sections on systems engineering tools and engineering design tools. Increasingly stringent environmental regulations are inducing a more holistic approach to environmental problems, shifting the focus from end-of-pipe pollution control to transforming industry to act as ecosystems with closed loops between wastes and resources. This mass balance approach to environmental problems pioneered by Ayers and Kneese45 and later called industrial ecology (IE) by Frosch and Gallopoulos46 is attracting considerable interest within the engineering and scientific community. With population pressures, congestion, resource depletion, and other indicators suggesting limitations on the assimilative capacity of the biosphere, source reduction, recycling, and other strategies to reduce waste generation (including emissions) and resource consumption are gaining greater attention. To devise and implement these strategies, firms must view their environmental impacts in a broad context from input supply and production through product distribution, use, and disposal. For instance, recent efforts by automobile companies to redesign internal combustion engines and to develop hydrogen fuel cell power vehicles are motivated in part by increasingly stringent air emission standards both here and abroad. The net environmental benefits of these technologies over existing transportation systems should be measured broadly to include environmental impacts during energy resource extraction, fuels processing, vehicle utilization, 45   R.U. Ayres and A.V. Kneese, "Production, Consumption, and Externalities," American Economic Review, Vol. 59, No. 3, pp. 282-297, 1969. 46   R.A. Frosch and N.E. Gallopoulos, "Strategies for Manufacturing," Scientific American, September, pp. 144-152, 1989.

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Retooling Manufacturing: Bridging Design, Materials, and Production and product disposal and recovery. There are several emerging methodologies for tracking environmental impacts within industrial systems. One approach is to quantify mass flows from source to sink for a material, element, chemical compound, or finished product at a point in time for a specific region, which is known as substance or mass flow analysis (MFA). For example, Socolow and Thomas47 examined flows of lead in the U.S. economy arguing that large-scale use of lead in electric cars should not be precluded because a nearly closed recycling system for lead–acid batteries that exists implies minimal health risks from lead exposure. Another common IE tool is life-cycle assessment (LCA), which the Society of Environmental Toxicology and Chemistry (SETAC) recommends to address the environmental implications of products and processes.48 SETAC views LCA as an objective process to evaluate the environmental burdens associated with a product, process, or activity. Mass balance analysis is employed in the inventory analysis component of an LCA, involving inventories of energy, materials, and wastes in raw material preparation, manufacturing, use, and disposal. For example, an LCA of an automobile involves estimating the resource use and effluents generated in the production of steel, glass, rubber, and other material components of the car. To this are added the resource and emissions inventory of the automobile assembly plant. The focus then shifts to consumers, how much fuel they consume and the emissions generated during the use of a car—that is, to quantify resources consumed and emissions generated in both fuel production and use, and the burdens (consumptions and emissions) associated with vehicle maintenance and repair such as new parts and oil changes. The final phase of the inventory examines the disposal of the vehicle, estimating what proportion is recycled and the composition of that flow. The inventory provides a more or less quantitative overview of the material and energy flows incurred in the product life cycle. Impact assessment, which follows, attempts to quantify potential impacts of the inventory on environmental and human health through metrics in a series of categories. Aggregating these impacts into metrics for decision making is perhaps one of the greatest challenges facing LCA.49 From this point, decision makers, such as product design and development teams, identify strategies to improve environmental performance. Development and implementation of these strategies involve a set of activities known in the industrial ecology community as design for the environment (DfE), for which Allenby50 identifies two general categories. The first includes generic efforts, such as green accounting systems and environmentally sensitive procurement policies. The second includes technological development, such as computerized DfE design tools integrated with automated design and manufacturing software. Life-Cycle Assessment The Society of Environmental Toxicology and Chemistry (SETAC)51 defines LCA as follows: 47   R. Socolow and V. Thomas, "The Industrial Ecology of Lead and Electric Vehicles," Journal of Industrial Ecology, Vol. 1, No. 1, pp. 13-36, 1997. 48   Society of Environmental Toxicology and Chemistry, A Technical Framework for Life-Cycle Assessment, SETAC, Washington, D.C., 1991. 49   Committee on Material Flows Accounting of Natural Resources, Products, and Residuals, National Research Council, Materials Count: The Case for Material Flows Analysis. The National Academies Press, Washington, D.C., 2002. 50   B.R. Allenby, Industrial Ecology: Policy Framework and Implementation, Prentice-Hall, Upper Saddle River, N.J., 1999, pp. 69-95. 51   Society of Environmental Toxicology and Chemistry, A Technical Framework for Life-Cycle Assessment, SETAC, Washington, D.C., 1991, p. 1.

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Retooling Manufacturing: Bridging Design, Materials, and Production The life-cycle assessment is an objective process to evaluate the environmental burdens associated with a product, process, or activity by identifying and quantifying energy and material usage and environmental releases, to assess the impacts of those energy and material uses and releases on the environment, and to evaluate and implement opportunities to effect environmental improvements. The assessment includes the entire life cycle of the product, process or activity, encompassing extracting and processing raw materials; manufacturing, transportation, and distribution; use/reuse/maintenance; recycling; and final disposal. This definition suggests four steps in LCA: goal and scope definition, resource and emissions inventory, impact assessment, and improvement analysis. The ideal is an objective assessment of the environmental implications of a well-defined production process and the identification of opportunities to improve environmental performance. Owens,52 however, argues that it is impossible to be entirely objective because most LCAs involve simplifying assumptions and subjective judgments. As the definition above states, LCA attempts to provide an objective assessment of the environmental implications of a well-defined production process and identifies opportunities to improve environmental performance. LCA studies should clearly define their goals. These goals may serve to improve environmental management and product design within the firm. Other goals include strategic concerns, such as demonstrating that a product or process has environmental attributes that exceed the competition. The definition of "cradle and grave" often varies depending upon the goal and scope of the analysis. In many cases, the cradle includes mining and raw material extraction while the grave is at the plant gate. One of the key steps in LCA is the emissions inventory. For many industrial processes, detailed inventory data by process are unavailable. In this case, some studies infer the data based upon input–output or mass balance relationships. A considerable number of subjective judgments enter this stage of the assessment, often buried in the details of the data compilation. In some cases, emissions judged to have no impact are not included in the inventory. This practice is misleading, although a mass balance could effectively uncover these emissions, depending of course on their magnitude. Conducting a mass balance requires engineering expertise and a detailed knowledge of the production process. Once the inventory is complete, the next step of LCA is impact assessment. Many industrial processes generate an array of air, water, and solid-waste emissions. Each of these categories in turn generates an array of impacts. Many studies classify these impacts into several categories, such as human health, air visibility, acid deposition, global climate change, and other impact categories. Since one pollutant can contribute to more than one impact category, LCA studies often develop metrics to measure the effect that each emission has on each impact category. As envisioned by SETAC, the final step in LCA is an analysis of how to improve the environmental performance of the production process. The analyst has the LCA inventory and estimates of the impacts across several different impact categories. LCA by itself, however, does not provide a framework for improvement analysis. The necessary decision framework should have two features. First, it should consider the cost of existing and alternative production technologies. In most situations, firms will not adopt environmentally beneficial technologies unless they generate significant cost savings over current technology.53 The second feature of 52   J.W. Owens, "Life-Cycle Assessment: Constraints on Moving from Inventory to Impact Assessment," Journal of Industrial Ecology, Vol. 1, No. 1, pp. 37-50, 1997. 53   It should be noted that the aerospace industry in Southern California, where the regulations of the South Coast Air Quality Management District are perhaps the most stringent in the world, has been very innovative in applying advanced manufacturing technology to develop such technologies as alternative paints, corrosion protection coatings, and adhesives to meet these very stringent requirements and at the same time save weight and reduce unit aircraft cost. For example, Boeing is now using new topcoat paint for the C-17 that has a lower volatile organic compound discharge rate and is lighter, more durable, and less expensive than traditional paints.

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Retooling Manufacturing: Bridging Design, Materials, and Production the decision framework is that it should include some method to aggregate environmental impacts, which impose indirect costs on the firm, perhaps by inducing onerous regulation, and costs on society. A broader definition of cost would include typical operating and capital costs, costs associated with environmental damage and savings from avoided disposal and regulation. The LCA inventory can provide a good basis to estimate these environmental costs. This last feature requires the development of an environmental metric. Considerable international effort has been expended to standardize the LCA process. Details of the standards can be found in ISO 14040, 14041, 14042, and 14043. These standards view LCA somewhat differently than SETAC; in fact, the phases of an LCA are goal and scope definition, inventory analysis, impact assessment, and finally interpretation. The ISO process sees LCA as having generally more iteration between the phases and also recommends certain practices pertaining to LCA objectives, public versus private studies, product comparisons, and allocation procedures. However, the basic process and intent of the two methods are the same and use of the SETAC framework here captures, with a little less complication, the essentials of LCA. The comprehensive nature of LCA is perhaps one of its flaws because the informational requirements can be daunting and expensive to meet. Estimating how these emissions affect human health, global warming, and other environmental problems is even more complex and is fraught with considerable uncertainty. Even with quantification of these uncertainties, impact assessment does not provide policy makers with a clear ranking of alternatives. This task requires an environmental metric that weights various environmental impacts. Several options exist for developing such metrics. One approach used by environmental economists essentially places a dollar value on impacts. This approach quantifies damage from environmental impacts so that the benefits of pollution reduction are the minimization or elimination of related monetary damages. Like the estimation of impacts, estimating the value of damage introduces another layer of uncertainty. While estimates of health costs associated with environmentally induced illness are easily documented, other impacts, such as ecosystem preservation and biodiversity, are inherently much more difficult to value. Another class of metrics avoids valuation and instead uses a variety of sustainability indices. The main drawback of these approaches is that arbitrary judgments may creep into the quantification of the sustainable standard. Regardless of what environmental metric or set of metrics is used, the technology adoption problem remains one of optimal choice under uncertainty. Many researchers have used operation research tools, such as linear programming models, to address these problems. For example, Considine et al. use a linear programming model to identify least-cost production and investment strategies for the steel industry under coke oven emission controls.54 Their model integrates engineering, economic, and environmental information. Other researchers have adopted a similar approach, such as Allen55 in his study of chlorine minimization strategies in the chemical industry. Design for the Environment A firm evaluating new technology must balance cost and strategic concerns with environmental performance. Cost depends upon the unit labor, energy, and material efficiency of the process as well as capital intensity. Cost is important because it ultimately relates to product affordability. Strategic aspects include breaking dependence upon suppliers of essential 54   T.J. Considine, G.A. Davis, and D.M. Marakovits, "Technological Change Under Residual Risk Regulation," Environmental and Resource Economics, Vol. 3, pp. 15-33, 1993. 55   D. Chang and D.T. Allen, "Minimizing Chlorine Use: Assessing the Trade-offs Between Cost and Chlorine Reduction in Chemical Manufacturing," Journal of Industrial Ecology, Vol. 1, No. 2, pp. 111-134, 1997.

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Retooling Manufacturing: Bridging Design, Materials, and Production intermediate materials, expansion into growth markets, and many other considerations. Increasingly, environmental performance is entering technology development and investment decisions. Evaluating the cost-effectiveness and environmental implications of different process and strategic choices facing a manufacturing plant can be complex. On the environmental side, the main source of complexity is the sheer volume of data from an LCA inventory. Another complication involves the interrelated nature of manufacturing operations. Changes in one unit process can affect the economics and environmental performance of downstream processes. Operations research (OR) tools provide a framework for organizing this information, identifying trade-offs, and making decisions. One subset of OR tools are engineering–economic process models. As the name suggests, these models integrate engineering detail about the production process with cost information. Environmental data concerning emissions are essentially engineering information. Building an engineering–economic process model typically begins with a definition of the production process at some chosen level of detail dictated by the availability of data about the process. For instance, at a very high level of aggregation, fiber optic production could be modeled to include slurry preparation, glass ingot production, cable extrusion, and product finishing. The level of aggregation depends upon the purpose of the model. If the intent is to understand the economic and environmental trade-offs of a new process, then all that is needed is to determine how that process would alter existing practice. The model of the existing system and its possible reconfigurations would include new technology as a process option. The next step in developing the model involves quantifying the input–output (IO) relations at each stage of the production process. Inputs include fuels, materials, supplies, maintenance, water, labor, and other inputs that vary with unit production levels. Outputs include the final product, recoverable byproducts, such as heat, steam, or offgases; and air, water, and solid waste emissions (or nonrecoverable byproducts). LCA emissions inventories taken for regulatory purposes are natural databases for estimating these latter components. In addition to the IO coefficients, constraints are another characteristic of the production process. One common constraint is capacity. For instance, how many tons of iron can a blast furnace produce in 1 year at average capacity utilization? Other constraints include final product demand, environmental emission standards, and material balances. The material balance constraints ensure that supplies of intermediate inputs are at least as large as the demand for them by downstream unit operations. The IO relations and constraints are essentially engineering information about the production process. The next layer requires economic information, including prices paid for purchased fuels, materials, and supplies. In addition, the analysis requires hourly wage rates on production workers and salaries for managerial and technical staff. Total operating costs equal the product of input requirements and prices paid for these inputs summed across all operations. The final step of the analysis requires specifying an objective function. There are several approaches available. First, one could specify a multiobjective function that essentially is a weighted function of operating and capital costs and environmental impacts with weights selected by the decision maker. Choosing the weights, however, often involves subjective judgments. Another approach is to specify an environmental damage function, which is the product of the environmental impacts and the dollar-per-kilogram damages. Under this specification, the objective is to minimize the sum of operating, capital, and environmental damage costs. These components—the process activities, their IO coefficients, the production constraints, and the objective function—constitute the engineering–economic process model. Life-cycle assessment information enters the definition of the process activities and the estimation of the IO coefficients. These coefficients include the indirect environmental impacts from upstream production activities. For example, purchasing a kilowatt of electricity may cost

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Retooling Manufacturing: Bridging Design, Materials, and Production four cents per kilowatt hour and indirectly contribute to global climate change, ground-level ozone impacts, and acid rain problems. In other words, the electricity-purchasing activity costs money and generates environmental impacts that impose costs on society. Subsequent processing activities involve purchasing factor inputs at market prices, using intermediate products that transfer from one process to another, and consuming common property environmental resources with values approximated by the procedures discussed above. The solution of an engineering–economic process model finds the mix of production activities that satisfies the objective function. Typically one of the first steps is to solve the model using the firm's current objective; for example, by minimizing operating costs and capital charges, and then comparing the optimal solution with current production levels for each unit process. If the constraints, prices, and IO coefficients are correct, then the solution should closely correspond with current practice. In essence, the process model provides a quantitative description of the production process. Some industries use process models for operation management, such as petroleum refiners who optimize their product mix based upon the cost and quality of their hydrocarbon inputs. Process models for DfE also provide a framework for examining the economics and environmental impacts of process design options. A modification of an existing process or a new process would become a process option in the model. Given market, capacity, and material balance constraints, the model would determine the least-cost mix of processes across different technologies. The challenge for this stage is to develop reliable estimates of the IO coefficients for the new technologies. Box 3-6 illustrates the use of such engineering–economic process models for steel production.56 In some cases, the design process is too complex and detailed to perform an overall system optimization. In these cases, process models can be used to optimize system components and less formal methods can be used to arrive at a final design that combines the environment, performance, and cost considerations. Product designers would then apply their own subjective weighting for these criteria, iterating toward a final design. Tool Development Needs Despite a mature state of development, life-cycle assessment is a time consuming and costly process. Moreover, the reliability of the results is unknown because the data and the methodology underlying environmental performance metrics are proprietary and, therefore, not subject to rigorous peer review. Although the International Organization for Standardization (ISO) has passed guidelines for conducting life-cycle assessment studies, two areas in need of further development include standardized peer reviewed databases and metrics development. The former is being addressed in North America by the National LCI Database project managed by Athena International. Some insights into the issues pertaining to metrics development can be found in a 1999 National Research Council report.57 The development of transparent and reproducible environmental performance metrics is clearly a necessary first step in bridging the gap between design for the environment and manufacturing. Engineers need to know the environmental design criteria. Developing one metric that aggregates many different environmental performance indicators is one approach. Another approach is to consider multiple criteria and subjectively balance them. In practice, however, designers need some notion of what the minimum acceptable environmental standards should be. Government standards, for example, attempt to do this by setting 56   T.J. Considine, C. Jablonowski, and D. Considine, "The Environment and New Technology Adoption in the U.S. Steel Industry," final report to National Science Foundation and Lucent Technologies, BES-9727296, May, 2001. 57   National Research Council, Industrial Environmental Performance Metrics: Challenges and Opportunities, Committee on Industrial Environmental Performance Metrics, National Academy Press, Washington, D.C., 1999.

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Retooling Manufacturing: Bridging Design, Materials, and Production Box 3-6 Case Study of the Environment and Process Design in Steel Production Steel mills use one of two types of furnaces to make new steel. Both furnaces recycle old steel into new, but each is used to create different products for varied applications. The first, the basic oxygen furnace, uses about 28 percent steel scrap to make new steel. The other 72 percent is molten iron produced from blast furnaces, which requires iron ore from mines, limestone from quarries, and coke from batteries of ovens. The furnace produces uniform and high-quality flat-rolled steel products used in cans, appliances, and automobiles. The other type of steel-making furnace, the electric arc furnace, melts virtually 100 percent steel scrap to make new steel. Steel minimills using these furnaces now produce nearly 50 percent of total U.S. steel production. This steel is used primarily to make products that have long shapes, such as steel plates, rebars, and structural beams. Steel minimills are far less capital intensive than integrated mills because they do not require blast furnaces and coke ovens. Their reliance on steel scrap also affords them an environmental advantage in lower consumption of energy and virgin material consumption. Minimills have entered the last domain of integrated steel, employing thin-slab casting that can yield relatively high quality sheet steel. This additional competitive force comes at a time when many integrated steel firms are seriously reevaluating their plants in light of the recent regulations controlling toxic emissions from coke ovens. Most existing methods of producing coke generate fugitive emissions that contain potentially carcinogenic substances, such as benzene soluble organics (BSOs). A variety of strategies, some entailing additional investment and/or higher operating costs, can reduce these emissions. Inland Steel built a large battery of coke ovens using the Thompson nonrecovery process, heralded as a possible clean technology breakthrough. This design allows the controlled burning of coal that destroys the BSOs and other potentially carcinogenic compounds contained in the offgases of the coking process. There are, however, relatively large amounts of sulfur dioxide emissions from the waste heat, which can be recovered via heat exchangers and used to produce steam for electricity generation. Several other iron- and steel-making technologies could either reduce or eliminate coke consumption. Pulverized coal injection, replacing up to 40 percent of the coke needed in iron making, is widely used in Europe, Asia, and Japan and is now gaining favor in the United States. Natural gas injection is another alternative technology. There are also two new steel-making technologies that could totally eliminate the need for coke. First, direct reduction, a coal or natural gas-based iron-making process, produces an iron substitute for scrap in electric arc furnaces. Another coke-eliminating option is the Corex process, which does not require coke and produces a large volume of waste heat that can be used to cogenerate electricity. Jewell is a nonpolluting coking technology used in steel making. Another coke steel-making process is Calderon whereby coal feeding and product recovery are employed in a closed process. To evaluate the economic and environmental performance of these technologies, an engineering– economic model of steel production is used. The model incorporates environmental emissions coefficients from an LCA of steel production from primary resource extraction to the plant gate. The model selects the optimal combination of activities to minimize cost subject to a number of constraints, including mass and energy balances for intermediate products. Substitute activities represent new technologies available for possible adoption. The model is for a specific steel plant with coefficients based upon actual operating performance. This analysis provides insights into the trade-offs between cost and environmental objectives, such as reducing greenhouse gas emissions, toxic discharges, and acidic residuals. The second application solves the model under two different definitions of cost: private and social cost, which includes private costs and those of the environmental damage, associated with LCA impacts. This approach permits determination of the socially optimal steel production technology mix achieved by internalizing environmental externalities. Following a sensitivity analysis, the third and final application examines the impact of carbon and virgin material taxes on technology choice in the steel industry. The incremental private and social costs of steel design options are shown below. On the basis of the total quantity of emissions in mass units, scrap-based steel production is environmentally superior to conventional integrated steel production. Using an economic valuation of the life-cycle environmental

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Retooling Manufacturing: Bridging Design, Materials, and Production impacts, however, indicates that these two technology paths are quite similar. In fact, using conventional damage cost estimates, electric arc furnace steel production imposes slightly greater environmental damage than does integrated production due to substantially greater emissions of SOx and NOx resulting from the electricity generated to supply these facilities. Hence, adopting a life-cycle perspective for technology assessment can yield some rather surprising conclusions. If producers explicitly minimize social cost, however, scrap-based steel production with natural gas cogeneration of electricity is optimal. This finding suggests that electricity supply decisions are a critical element in assessing the economic and environmental performance of new steel production technologies. Some of the Incremental Private and Social Costs of Steel Design Options   Jewell Corex Scrap Electric Scrap-DR Electric Calderon New capital expenditures 216.6a 575.42 437.41 503.17 246,32 Labor and capital 32.40 90.78 –89.66 –72.73 0.48 Energy –4.11 30.69 –20.07 –15.10 3.02 Materials 0.00 –35.89 85.57 63.34 0.82 Total operating cost 28.29 85.59 –24.19 –24.49 4.32 (less byproduct sales) –0.16 –3.07 5.58 5.19 0.00 Net operating cost 28.13 82.51 –18.57 –19.30 4.32 Environmental damage 2.34 132.84 57.39 63.34 –16.58 Total social cost 30.63 218.43 33.23 38.85 –12.26 aMillions of 1998 dollars. standards for emissions of air pollutants, such as sulfur dioxide, nitrous oxides, and particulate matter. Standards, however, are often considered an inefficient way to improve the environment because they stifle technological innovation. There is also a need for integrating life-cycle assessment tools with operations-research-based decision science models so that cost, technical, and environmental performance can be optimized. For this to occur, however, environmental performance metrics must be specified and measured. Decision makers need a measure of the environmental bottom line, not an array of different environmental impacts that are difficult to value individually, much less collectively. Balancing various technical performance measures in design is a similar problem. In this case, establishing minimum acceptable standards helps simplify the decision problem in which the choice becomes a constraint or requirement. Unfortunately, the societal consensus reflected in environmental standards is often at odds with companies' attempts to maintain their fiduciary responsibility to stockholders for company profitability. Another need for life-cycle assessment is to simplify and standardize its application. A modular approach could be one possibility to simplify and reduce LCA cost in which industry has off-the-shelf modules that provide LCA impacts for a material or transformation process under consideration. Recommendation 5. Life-Cycle Assessment: The Department of Defense should develop tools and databases that enable life-cycle costs and environmental impact to be quantified and integrated into design and manufacturing processes. Establishing and maintaining peer-reviewed databases for environmental emissions and impacts of various materials and manufacturing processes will be critical for the government to integrate these factors into acquisition processes. Environmental performance metrics that combine multiple impacts are most useful for design

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Retooling Manufacturing: Bridging Design, Materials, and Production decisions. The development of high-level optimization methods can allow analysis of the trade-offs between cost, performance, schedule, and environmental impact. COMMON THEMES Different disciplinary areas are directly involved in the design and manufacturing process—systems engineering, engineering design, materials science, manufacturing, and life-cycle assessment. Other supporting infrastructures are involved indirectly and affect all of these specific fields in an overarching way. As outsourcing becomes more prevalent, and as many of these tasks are sent overseas, maintaining design and manufacturing capability in the United States is a real concern. It is essential that the United States continue to produce students who are trained for design, manufacturing, and systems engineering. It must also maintain a manufacturing capability in this country that employs these graduates. Engineering Education The availability of an educated domestic workforce is crucial to the quality of life, to the national defense, and to the economic security and competitiveness of the nation, and a key part of this workforce is in the manufacturing sector. The education and training of tomorrow's workforce become even more critical when one considers that the entire design and manufacturing field has expanded greatly in knowledge in recent years and will continue to do so, most likely at an even faster pace, in the foreseeable future. Information technology is rapidly enhancing the process of communication between customers, engineers, and manufacturers. The broadening of the arena requires an integrated and well-balanced science and engineering education that covers systems, design, materials, and manufacturing. An integrated approach for traditional educational institutions as well as for certification programs for practitioners will ensure that the workforce is able to use the new tools and strategies for efficient product realization. Recommendation 6. Engineering Education: The Department of Defense should invest in the education and training of future generations of engineers who will have a thorough understanding of the concepts and tools necessary to bridge design and manufacturing. Integrating knowledge of virtual manufacturing into university curricula to train new engineers can help them use tools to bridge design and manufacturing. To ensure an adequate supply of such trained engineers, the DoD can help to develop programs to increase the quality and the number of graduating engineers available to work in these fields. It is also critical to retain U.S. capability in contributing disciplines, such as materials science and engineering.